| Subject ID | test |
| Sex | MALE |
| Dominant hand | LEFT |
| Test date and time | 2023-02-09 22:01 |
| Test battery | Circle, Spiral, Elel, FITTS Short Modified, FITTS Long Modified, ZigZag, ZigZag Offset |
| Operator comment |
Parkinson’s Disease Evaluation
Important
This report is intended to assist qualified Health Care Profesionals (HCP) in the assessment of an individual referred under the suspicion of having Parkinson’s Disease.
Clinical Context
This report presents several AI metrics derived from objective measures from individuals performing a battery of test using Manus Neurodynamica NeuroMotor PenTM.
These presented metrics combine factors from detailed measurement recordings made whilst the individual performs a battery of well established neurological test tasks.
The metrics have been assessed in a UK reference population and an individual’s results are presented in this clinical context. The HCP should review Clinical,Reference, Study et al [1] to establish applicability and limitations.
The information in this report should be used in the context of a full neurological assessment conducted to the current standard of care practices to establish a diagnosis.
Subject and Recording Details
Overall Assessment
Subject performance similar to PD population (recommend review of report details)
Clinical context
In the clinical reference population, 29 individuals with a value less than 0.62 were subsequently diagnosed with PD. That is, 69.05% of the PD diagnoses in the study.
Additionally, 0 individuals with a value greater or equal to 0.62 were subsequently diagnosed as not having PD. That is, 0.0% of the non PD diagnoses in the study.
Note
We need to look into this whole ‘confidence’ thing. It is really confusing. In the above plot I have shown 1.0 - reported conf for the ‘predicted as non PD individuals’. I am not happy with the obvious 0.5 clipping above. We would expect this in a classifier operating on it’s own training data and not a real world clinical test.
Symptom Scores
These mini boxplots show the scores in a clinical context. Currently against the ‘Walker study’ data. A bigger pool would be much better (so max 83 individuals, usually lower if raw data did not result in successful classification).
Micrographia Features
The micrographia symptom assessment is derived from a combination of factors in the elel task.
{'FN': 19, 'TN': 14, 'TP': 23, 'FP': 16}Tremor Features
{'FN': 39, 'TN': 27, 'TP': 3, 'FP': 3}Bradykinesia
{'FN': 2, 'TN': 2, 'TP': 40, 'FP': 28}Spatial Accuracy
{'FN': 5, 'TN': 3, 'TP': 37, 'FP': 27}Test Battery Details
2023-03-09 16:39:34.078 | INFO | neuromotor_pen.data:_parse_header:693 - Loading New Data Version...ManusData_pd_test_09022023100926.JSONCircle
Circle Segment 1
Duration 3.8 s, Accuracy Estimate 2.006 (lower is better)
Circle Segment 2
Duration 2.76 s, Accuracy Estimate 2.777 (lower is better)
Circle Segment 3
Duration 2.76 s, Accuracy Estimate 2.528 (lower is better)
Circle Segment 4
Duration 2.76 s, Accuracy Estimate 2.202 (lower is better)
Circle Segment 5
Duration 2.36 s, Accuracy Estimate 2.819 (lower is better)
Circle Segment 6
Duration 2.44 s, Accuracy Estimate 2.874 (lower is better)
Circle Segment 7
Duration 2.12 s, Accuracy Estimate 4.665 (lower is better)
Circle Segment 8
Duration 2.4 s, Accuracy Estimate 2.43 (lower is better)
Circle Segment 9
Duration 2.36 s, Accuracy Estimate 2.818 (lower is better)
Circle Segment 10
Duration 2.16 s, Accuracy Estimate 4.653 (lower is better)
Spiral
Spiral Segment 1
Duration 9.68 s, Accuracy Estimate 2.316 (lower is better)
Spiral Segment 2
Duration 8.96 s, Accuracy Estimate 2.175 (lower is better)
Spiral Segment 3
Duration 9.12 s, Accuracy Estimate 2.266 (lower is better)
Spiral Segment 4
Duration 9.44 s, Accuracy Estimate 2.291 (lower is better)
Spiral Segment 5
Duration 9.4 s, Accuracy Estimate 1.949 (lower is better)
Spiral Segment 6
Duration 8.16 s, Accuracy Estimate 2.168 (lower is better)
Spiral Segment 7
Duration 7.52 s, Accuracy Estimate 2.307 (lower is better)
Spiral Segment 8
Duration 8.48 s, Accuracy Estimate 2.202 (lower is better)
Spiral Segment 9
Duration 8.2 s, Accuracy Estimate 2.059 (lower is better)
Spiral Segment 10
Duration 12.2 s, Accuracy Estimate 1.597 (lower is better)
Elel
Elel Segment 1
Elel Segment 2
Elel Segment 3
Elel Segment 4
Elel Segment 5
Elel Segment 6
Elel Segment 7
Elel Segment 8
Elel Segment 9
Elel Segment 10
FITTS Short Modified
FITTS Long Modified
ZigZag
ZigZag Segment 1
Duration 6.56 s, Accuracy Estimate 4.375 (lower is better)
ZigZag Segment 2
Duration 5.6 s, Accuracy Estimate 4.553 (lower is better)
ZigZag Segment 3
Duration 5.6 s, Accuracy Estimate 4.149 (lower is better)
ZigZag Segment 4
Duration 5.8 s, Accuracy Estimate 3.603 (lower is better)
ZigZag Segment 5
Duration 5.52 s, Accuracy Estimate 4.406 (lower is better)
ZigZag Offset
ZigZag Offset Segment 1
Duration 5.32 s, Accuracy Estimate 0.059 (lower is better)
ZigZag Offset Segment 2
Duration 4.8 s, Accuracy Estimate 0.048 (lower is better)
ZigZag Offset Segment 3
Duration 4.84 s, Accuracy Estimate 0.05 (lower is better)
ZigZag Offset Segment 4
Duration 5.0 s, Accuracy Estimate 0.05 (lower is better)
ZigZag Offset Segment 5
Duration 4.28 s, Accuracy Estimate 0.096 (lower is better)
Appendices
Misc
Currently a dumping ground for things that could be included or previous output style.
Note
Putting all the results out here but will not be in a final report.
| HiSpec | {‘HiSpec_class’: ‘NOT PD’, ‘HiSpec_score’: 0.63} |
| RanFor | {‘RanFor_class’: ‘PD’, ‘RanFor_score’: 0.62} |
| BM_May22 | {‘BM_May22_class’: ‘PD’, ‘BM_May22_score’: 0.6581378343237094} |
| BM_HC_Sep22 | {‘BM_HC_Sep22_class’: ‘Patient’, ‘BM_HC_Sep22_score’: 0.7032407530939824} |
| BM_PD_Sep22 | {‘BM_PD_Sep22_class’: ‘PD’, ‘BM_PD_Sep22_score’: 0.7137867214078727} |
